Electrochemical Investigation of Azurin Thermodynamic and Adsorption Properties at Monolayer-Protected Cluster Film Assemblies – Evidence for a More Homogeneous Adsorption Interface

Thermodynamic and adsorption properties of protein monolayer electrochemistry (PME) are examined for Pseudomonas aeruginosa azurin (AZ) immobilized at an electrode modified with a networked film of monolayer-protected clusters (MPCs) to assess if nanoparticle films of this nature offer a more homogeneous adsorption interface compared to traditional self-assembled monolayer (SAM) modified electrodes. Specifically, electrochemistry is used to assess properties of surface coverage, formal potential, peak broadening, and electron transfer (ET) kinetics as a function of film thickness. The modification of a surface with dithiol-linked films of MPCs (Au225C675) provides a more uniform binding interface for AZ that results in voltammetry with less peak broadening (mV) compared to SAMs (\u3e120–130 mV). Improved homogeneity of the MPC interface for protein adsorption is confirmed by atomic force microscopy imaging that shows uniform coverage of the gold substrate topography and by electrochemical analysis of film properties during systematic desorption of AZ, which indicates a more homogeneous population of adsorbed protein at MPC films. These results suggest MPC film assemblies may be used in PME to provide greater molecular level control of the protein adsorption interface, a development with applications for strategies to study biological ET processes as well as the advancement of biosensor technologies

Distance Dependence of Electron Transfer Kinetics for Azurin Protein Adsorbed to Monolayer Protected Nanoparticle Film Assemblies

The distance dependence and kinetics of the heterogeneous electron transfer (ET) reaction for the redox protein azurin adsorbed to an electrode modified with a gold nanoparticle film are investigated using cyclic voltammetry. The nanoparticle films are comprised of nonaqueous nanoparticles, known as monolayer-protected clusters (MPCs), which are covalently networked with dithiol linkers. The MPC film assembly serves as an alternative adsorption platform to the traditional alkanethiolate self-assembled monolayer (SAM) modified electrodes that are commonly employed to study the ET kinetics of immobilized redox proteins, a strategy known as protein monolayer electrochemistry. Voltammetric analysis of the ET kinetics for azurin adsorbed to SAMs of increasing chain length results in quasi-reversible voltammetry with significant peak splitting. We observed rate constants (k°ET) of 12−20 s−1 for the protein at SAMs of shorter alkanethiolates that decays exponentially (β = 0.9/CH2 or 0.8/Å) at SAMs of longer alkanethiolates (9−11 methylene units) or an estimated distance of 1.23 nm and is representative of classical electronic tunneling behavior over increasing distance. Azurin adsorbed to the MPC film platforms of increasing thickness results in reversible voltammetry with very little voltammetric peaks splitting and nearly negligible decay of the ET rate over significant distances up to 20 nm. The apparent lack of distance dependence for heterogeneous ET reactions at MPC film assemblies is attributed to a two-step mechanism involving extremely fast electronic hopping through the MPC film architecture. These results suggest that MPC platforms may be used in protein monolayer electrochemistry to create adsorption platforms of higher architecture that can accommodate greater than monolayer protein coverage and increase the Faradaic signal, a finding with significant implications for amperometric biosensor design and development

Genetic and environmental contributions to neonatal brain structure: A twin study

Twin studies have found that global brain volumes, including total intracranial volume (ICV), total gray matter, and total white matter volumes are highly heritable in adults and older children. Very little is known about genetic and environmental contributions to brain structure in very young children and whether these contributions change over the course of development. We performed structural imaging on a 3T MR scanner of 217 neonatal twins, 41 same-sex monozygotic, 50 same-sex dizygotic pairs, and 35 “single” twins—neonates with brain scans unavailable for their co-twins. Tissue segmentation and parcellation was performed, and structural equation modeling was used to estimate additive genetic, common environmental, and unique environmental effects on brain structure. Heritability of ICV (0.73) and total white matter volume (0.85) was high and similar to that described in older children and adults; the heritability of total gray matter (0.56) was somewhat lower. Heritability of lateral ventricle volume was high (0.71), whereas the heritability of cerebellar volume was low (0.17). Comparison with previous twin studies in older children and adults reveal that three general patterns of how heritability can change during postnatal brain development: (1) for global white matter volumes, heritability is comparable to reported heritability in adults, (2) for global gray matter volume and cerebellar volume, heritability increases with age, and (3) for lateral ventricle volume, heritability decreases with age. More detailed studies of the changes in the relative genetic and environmental effects on brain structure throughout early childhood development are needed

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.Fil: Mitra, Anish. Washington University School Of Medicine In St. Louis; Estados UnidosFil: Snyder, Abraham Z.. Washington University School Of Medicine In St. Louis; Estados UnidosFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Laufs, Helmut. Christian-albrechts-universitat Zu Kiel; AlemaniaFil: Elison, Jed. University of Minnesota; Estados UnidosFil: Emerson, Robert W.. University of North Carolina; Estados UnidosFil: Shen, Mark D.. University of North Carolina; Estados UnidosFil: Wolff, Jason J.. University of Minnesota; Estados UnidosFil: Botteron, Kelly N.. Washington University School Of Medicine In St. Louis; Estados UnidosFil: Dager, Stephen. University Of Washington, Seattle; Estados UnidosFil: Estes, Annette M.. University Of Washington, Seattle; Estados UnidosFil: Evans, A.C.. McGill University. Montreal Neurological Institute and Hospital; CanadáFil: Gerig, Guido. University of New York; Estados UnidosFil: Hazlett, Heather C.. University of North Carolina; Estados UnidosFil: Paterson, Sarah J.. University of Pennsylvania; Estados UnidosFil: Schultz, Robert T.. University of Pennsylvania; Estados UnidosFil: Styner, Martin A.. University of North Carolina; Estados UnidosFil: Zwaigenbaum, Lonnie. University of Alberta; CanadáFil: Chappell, C.. Ibis Network Pi; Estados UnidosFil: Estes, A.. University Of Washington, Seattle; Estados UnidosFil: Shaw, D.. University Of Washington, Seattle; Estados UnidosFil: Botteron, K.. University Of Washington, Seattle; Estados UnidosFil: McKinstry, R.. University Of Washington, Seattle; Estados UnidosFil: Constantino, J.. University Of Washington, Seattle; Estados UnidosFil: Pruett, J.. University Of Washington, Seattle; Estados UnidosFil: Schultz, R.. The Children?s Hospital Of Philadelphia; Estados UnidosFil: Paterson, S.. The Children?s Hospital Of Philadelphia; Estados UnidosFil: Collins, D.L.. McGill University. Montreal Neurological Institute and Hospital; CanadáFil: Pike, G.B.. McGill University. Montreal Neurological Institute and Hospital; CanadáFil: Fonov, V.. McGill University. Montreal Neurological Institute and Hospital; CanadáFil: Kostopoulos, P.. McGill University. Montreal Neurological Institute and Hospital; CanadáFil: Dasso, Sergio Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Styner, M.. The University Of North Carolina System; Estados UnidosFil: Gu, H.. Statistical Analysis Core; Estados UnidosFil: Schlaggar, Bradley L.. Washington University School Of Medicine In St. Louis; Estados UnidosFil: Piven, Joseph. University of North Carolina; Estados UnidosFil: Pruett, John R.. Washington University School Of Medicine In St. Louis; Estados UnidosFil: Raichle, Marcus. Washington University School Of Medicine In St. Louis; Estados Unido

Early brain development in infants at high risk for autism spectrum disorder

Brain enlargement has been observed in children with Autism Spectrum Disorder (ASD), but the timing of this phenomenon and its relationship to the appearance of behavioral symptoms is unknown. Retrospective head circumference and longitudinal brain volume studies of 2 year olds followed up at age 4 years, have provided evidence that increased brain volume may emerge early in development.(1, 2) Studies of infants at high familial risk for autism can provide insight into the early development of autism and have found that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life(3,4). These observations suggest that prospective brain imaging studies of infants at high familial risk for ASD might identify early post-natal changes in brain volume occurring before the emergence of an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that cortical surface area hyper-expansion between 6-12 months of age precedes brain volume overgrowth observed between 12-24 months in the 15 high-risk infants diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep learning algorithm primarily using surface area information from brain MRI at 6 and 12 months of age predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81%, sensitivity of 88%). These findings demonstrate that early brain changes unfold during the period in which autistic behaviors are first emerging